X-13ARIMA-SEATS Seasonal Adjustment Program

Seasonal Adjustment to Facilitate Forecasting: Empirical Results

William R. Bell ⁽¹⁾ and Ekaterina Sotiris ⁽²⁾

ABSTRACT:

In this paper we consider how well seasonal adjustment methods (X-11 and ARIMA model- based), and certain of their variations, satisfy one objective of seasonal adjustment: facilitating short-term forecasting of nonseasonal movements in time series. We do this via an empirical study using a number of seasonal time series of major U.S. economic aggregates. For these series we examine how forecast accuracy is affected by the following choices: (1) alternative choices of simple models for forecasting the seasonally adjusted series (or trend estimates); (2) use of seasonally adjusted series versus trend estimates; (3) use of time series of unrevised versus time series of revised seasonally adjusted data; (4) use of X-11 versus ARIMA model-based adjustment; and (5) use of seasonally adjusted data in forecasting versus directly forecasting the unadjusted series.

KEYWORDS:

X-11 seasonal adjustment, ARIMA model-based seasonal adjustment, seasonal adjustment revision, trend estimation

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⁽¹⁾ William R. Bell is Senior Mathematical Statistician for Small Area Estimation, U.S. Census Bureau, 4600 Silver Hill Road, Washington, DC 20233. email : william.r.bell@census.gov

⁽²⁾ Ekaterina Sotiris is a student at the University of Maryland and Statistician, U. S. Census Bureau email: ekaterina.sotiris@census.gov